3 papers
cs.CL2026
Evaluating Modern Large Language Models on Low-Resource and Morphologically Rich Languages:A Cross-Lingual Benchmark Across Cantonese, Japanese, and Turkish
Chengxuan Xia, Qianye Wu, Hongbin Guan +3
Large language models (LLMs) have achieved impressive results in high-resource languages like English, yet their effectiveness in low-resource and morphologically rich languages re…
cs.MA2026
Parallelism Meets Adaptiveness: Scalable Documents Understanding in Multi-Agent LLM Systems
Chengxuan Xia, Qianye Wu, Sixuan Tian +1
Large language model (LLM) agents have shown increasing promise for collaborative task completion. However, existing multi-agent frameworks often rely on static workflows, fixed ro…
cs.IR2025
AI-Driven Sentiment Analytics: Unlocking Business Value in the E-Commerce Landscape
Qianye Wu, Chengxuan Xia, Sixuan Tian
The rapid growth of e-commerce has led to an overwhelming volume of customer feedback, from product reviews to service interactions. Extracting meaningful insights from this data i…